Probability Commons^™

A Superposed Log-Linear Failure Intensity Model For Repairable Artillery Systems, Byeong Min Mun, Suk Joo Bae, Paul Kvam

Department of Math & Statistics Faculty Publications

This article investigates complex repairable artillery systems that include several failure modes. We derive a superposed process based on a mixture of nonhomogeneous Poisson processes in a minimal repair model. This allows for a bathtub-shaped failure intensity that models artillery data better than currently used methods. The method of maximum likelihood is used to estimate model parameters and construct confidence intervals for the cumulative intensity of the superposed process. Finally, we propose an optimal maintenance policy for repairable systems with bathtub-shaped intensity and apply it to the artillery-failure data.